table-transformer-detection
Table Transformer (DETR) model trained on PubTables1M. It was introduced in the paper PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents by Smock et al. and first released in this repository.
Params
30 M
Context
1,024
Downloads 30d
596 K
Likes
428
Download history
daily snapshots · 55 days
▲ 262 K in the last 30 days (30.5%)
826 K585 K
Aug 22Sep 1Sep 11Sep 20
1.2 M585 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.1 GB | 0.6 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- TableTransformerForObjectDetection
- Parameters
- 30 M
- Tensor type
- F32
- Context length
- 1,024
- Licence
- mit
- First seen on the Hub
- 2022-10-14
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any object-detection model